Pasi Liljeberg
Professor, Head of Department
pasi.liljeberg@utu.fi +358 29 450 2469 +358 40 543 3722 Vesilinnantie 5 Turku Työhuone: 1st floor ORCID-tunniste: https://orcid.org/0000-0002-9392-3589 |
Biomedical engineering, Internet of Things, edge computing, Wearable sensors, Digital health technology, Health data analytics, Approximate and adaptive computing,
Research interest fall to the areas of biomedical engineering, health technology and edge computing. Please see also: https://healthtech.utu.fi
Pasi Liljeberg received MSc and PhD degrees in information and communication technology from the University of Turku, Turku, Finland, in 1999 and 2005, respectively. He received Adjunct professorship in embedded computing architectures in 2010. Currently he is working as a full professor in University of Turku in the Digital Health Technology unit. At the same time he serves as head of the Department of Computing, Faculty of Technology, University of Turku. His research interests are biomedical engineering, Internet of Things, edge computing, approximate and adaptive computing, wearable sensors, digital health technology and health data analytics. Liljeberg is the (co-)author of around 300 peer-reviewed publications.
My research interest fall in the field of biomedical engineering, health technology and Internet-of-Things. This is in the context wearable biomedical, wearable technology, applied machine learning, bio-signal processing, health informatics and edge computing. Special attention is paid to novel biomedical sensing applications, wearable computing, analytics, informatics, communication, and networking paradigms, especial focus onhealthcare and wellbeing applications.
Teaching interest in the field of Health Technology in general.
- Robust PPG Peak Detection Using Dilated Convolutional Neural Networks (2022)
- Sensors
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Trends in Heart Rate and Heart Rate Variability During Pregnancy and the 3-Month Postpartum Period: Continuous Monitoring in a Free-living Context (2022)
- JMIR mHealth and uHealth
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Approximate Feature Extraction for Low Power Epileptic Seizure Prediction in Wearable Devices (2021) 2021 IEEE Nordic Circuits and Systems Conference (NorCAS) Taufique Zain, Kanduri Anil, Bin Altaf Muhammad Awais, Liljeberg Pasi
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Energy-Performance Co-Management of Mixed-Sensitivity Workloads on Heterogeneous Multi-core Systems (2021)
- Proceedings of the Asia and South Pacific Design Automation Conference
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Lightweight Photoplethysmography Quality Assessment for Real-time IoT-based Health Monitoring using Unsupervised Anomaly Detection (2021)
- Procedia Computer Science
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Long-Term IoT-Based Maternal Monitoring: System Design and Evaluation (2021)
- Sensors
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Pain assessment tool with electrodermal activity for postoperative patients: Method validation study (2021)
- JMIR mHealth and uHealth
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Pain Recognition With Electrocardiographic Features in Postoperative Patients: Method Validation Study (2021)
- Journal of Medical Internet Research
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Pregnant women's daily patterns of well-being before and during the COVID-19 pandemic in Finland: Longitudinal monitoring through smartwatch technology (2021)
- PLoS ONE
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - UBAR: User- and Battery-aware Resource Management for Smartphones (2021)
- ACM Transactions in Embedded Computing Systems
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä )



